MM/PBSA (Molecular Mechanics/Poisson–Boltzmann Surface Area) and MM/GBSA (Molecular Mechanics/Generalized Born Surface Area) are computational methods used to estimate the binding free energy of biomolecular complexes, such as protein–ligand or protein–protein interactions. These approaches combine molecular mechanics energies for protein and ligand atoms with solvation terms calculated using either the Poisson–Boltzmann equation (PBSA) or the Generalized Born model (GBSA). PBSA and GBSA model solvent implicitly, thus are more computational efficient than energy perturbation methods that use explicit solvent models. Because protein and ligand atoms are modeled through MM, MM/PBSA and MM/GBSA provide a balance between accuracy and computational efficiency. The GB SA is an approximation of the PB SA, so it is the most efficient, but also the least accurate.
Importance in Computational Drug Discovery:
- Enables rapid and cost-effective estimation of binding affinities for large sets of compounds after molecular docking or molecular dynamics simulations.
- Facilitates ranking and prioritization of drug candidates based on predicted binding free energies.
- Supports lead optimization by quantifying the energetic contributions of specific ligand modifications.
- Complements experimental binding assays, guiding hypothesis-driven design and reducing experimental workload.
- Integrates with molecular dynamics workflows to capture dynamic and entropic effects in binding.
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